城市网约车与弱势交通参与者事故的时空特征与归因机制

Spatio-Temporal Characteristics and Attribution Mechanism of Accidents between Urban Ride-Hailing and Vulnerable Traffic Participants

摘要: 解析网约车与弱势交通参与者(VRU)在复杂路网中的冲突机制，是系统提升城市交通韧性的关键。本文基于成都市113起网约车事故数据，构建“冲突模态–时空环境–行为归因”三维解构模型。数据分析表明：第一，因物理隔离缺失与驾驶员反应迟滞的重叠，涉及行人横穿的事故(占比42.7%)，其致命率显著高于二轮车交叉冲突；第二，事故在几何拓扑上高度向四枝交叉口和早晚高峰期收敛，映射出派单算法压迫下的认知负荷饱和；第三，电驱动车型在低附着环境下的瞬时扭矩响应放大，构成了系统性的底层隐患。网约车事故是“阈值偏移–隐匿规则固化–反馈滞后”系统链条断裂的产物，据此本文提出了涵盖物理路网修复、算法强制熔断及线控底盘自适应等跨主体干预架构设想。

Abstract: Analyzing the conflict mechanism between ride-hailing and vulnerable traffic participants (VRUs) in complex road networks is the key to systematically improving urban traffic resilience. Based on the data of 113 ride-hailing accidents in Chengdu, this paper constructs a three-dimensional deconstruction model of “conflict mode-spatio-temporal environment-behavior attribution”. The data analysis shows that: first, due to the overlap between the lack of physical isolation and the driver’s delay, the fatality rate of accidents involving pedestrian crossing (accounting for 42.7%) is significantly higher than that of two-wheeled vehicle cross-collisions. Second, the accident converges to the intersection of the four branches and the morning and evening peak periods in the geometric topology, which reflects the saturation of the cognitive load under the pressure of the dispatch algorithm. Third, the instantaneous torque response of electric drive models in a low adhesion environment is amplified, which constitutes a systemic underlying hidden danger. The online car-hailing accident is the product of the system chain rupture of “threshold shift-concealment rule solidification-feedback lag”, so this paper proposes a cross-subject intervention architecture covering physical road network repair, algorithm forced fuse and wire-controlled chassis adaptation.